Techniques for compensating for ego-velocity and target velocity in the digitally-sampled target signal

ABSTRACT

A method of compensation in a light detection and ranging (LIDAR) system. The method includes generating a digitally-sampled target signal. The method also includes compensating for ego-velocity and target velocity in the digitally-sampled target signal based on an estimated ego-velocity and an estimated target velocity to produce a compensated digitally-sampled target signal.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/335,530 filed on Jun. 1, 2021, which claims priority from and thebenefit of U.S. Patent Application No. 63/087,432 filed on Oct. 5, 2020;and U.S. Patent Application No. 63/089,886 filed on Oct. 9, 2020; theentire contents of which are incorporated herein by reference in theirentirety.

FIELD OF INVENTION

The present disclosure is related to light detection and ranging (LIDAR)systems.

BACKGROUND

Conventional Frequency-Modulated Continuous-Wave (FMCW) LIDAR systemsinclude several possible phase impairments such as laser phase noise,circuitry phase noise, flicker noise that the driving electronics injecton a laser, drift over temperature/weather, and chirp rate offsets.These impairments cause loss in probability of detection, increasedfalse alarm, range/velocity bias and increase the error in estimatedtarget range/velocity.

SUMMARY

The present disclosure describes various embodiments of LIDAR systemsand methods that, among other things, mitigate phase impairments may beexperienced by LIDAR systems. Embodiments of the present inventioninclude the functionality to introduce a Doppler compensated phaseimpairment correction.

According to one aspect, the present disclosure relates to a method ofcompensating for phase impairments in a light detection and ranging(LIDAR) system. The method includes compensating for ego-velocity andtarget velocity in the digitally-sampled target signal based on anestimated ego-velocity and an estimated target velocity to produce acompensated digitally-sampled target signal. The method may also includeperforming a phase impairment correction on the compensateddigitally-sampled target signal for transmission to a point cloud. In anembodiment, the method also includes determining the ego-velocity of theLIDAR system, wherein the ego-velocity is a velocity of the LIDAR systemcalculated based on neighboring objects measured using one or moremotion sensors. In an embodiment, compensating for the ego-velocity andtarget velocity in the digitally-sampled target signal includes:applying a first frequency shift to the digitally-sampled target signal,the first frequency shift being a function of an ego-velocity of theLIDAR system; and applying a second frequency shift to thedigitally-sampled target signal, the second frequency shift being aconjugate of the first frequency shift. In an embodiment, the methodalso includes generating a digitally-sampled reference signal using areference beam transmitted through a fiber delay device and a secondphoto-detector; wherein performing the phase impairment correction onthe digitally-sampled target signal includes correcting for phaseimpairments introduced into the digitally-sampled target signal by theLO beam and by the return signal. In an embodiment, the method alsoincludes determining a velocity of neighboring points in a vicinity ofthe target; and generating the estimated target velocity based on thevelocity of neighboring points. In an embodiment, determining thevelocity of neighboring points includes: running a standard corrector onall neighboring points; and estimating a statistic of the velocity ofneighboring points. In an embodiment, the method also includesdetermining a velocity of previous points of the target within a pointcloud; and generating the estimated target velocity based on thevelocity of previous points. In an embodiment, determining the velocityof previous points of the target within the point cloud includesdetermining a velocity of an immediately preceding point in a same scanline, determining a velocity of points from previous scan lines, ordetermining a velocity of points from previous scan-frames.

According to another aspect, the present disclosure relates to a LIDARsystem including: an optical beam source to transmit a first opticalbeam to a target; a first photo detector to receive a return signal fromthe target and a LO beam and generate a digitally-sampled target signal;a fiber delay device having a known length and coupled to the opticalbeam source; a second detector coupled to the fiber delay device togenerate a digitally-sampled reference signal using a reference beamtransmitted through the fiber delay device; at least two frequencyshifters to compensate for ego-velocity and target velocity in thedigitally-sampled target signal based on an estimated ego-velocity andestimated target velocity; and a deskew filter to perform a phaseimpairment correction on the digitally-sampled target signal. In anembodiment, the ego-velocity is a velocity of the LIDAR system withrespect to neighboring objects measured using one or more motionsensors. In an embodiment, the frequency shifters include: a firstfrequency shifter to apply a first frequency shift to thedigitally-sampled target signal, the first frequency shift being afunction of an ego-velocity of the LIDAR system; and a second frequencyshifter to apply a second frequency shift to the digitally-sampledtarget signal, the second frequency shift being a conjugate of the firstfrequency shift. In an embodiment, the phase impairment correction onthe digitally-sampled target signal corrects for phase impairmentsintroduced into the digitally-sampled target signal by the LO beam andby the return signal. In an embodiment, the LIDAR system is alsoconfigured to determine the estimated target velocity based on avelocity of neighboring points in a vicinity of the target. In anembodiment, the LIDAR system determines the velocity of neighboringpoints by running a standard corrector on all neighboring points; andestimating a statistic of the velocity of neighboring points. In anembodiment, the LIDAR system is also configured to determine theestimated target velocity based on a velocity of previous points of thetarget within a point cloud. In an embodiment, the LIDAR systemdetermines the velocity of previous points by determining a velocity ofan immediately preceding point in a same scan line, determining avelocity of points from previous scan lines, or determining a velocityof points from previous scan-frames.

According to another aspect, the present disclosure relates to a methodof compensating for phase impairments in a LIDAR system. The methodincludes transmitting a first optical beam to a target from the LIDARsystem; receiving, at the LIDAR system, a return signal from the targetat a first photo detector; generating a digitally-sampled referencesignal using a reference beam transmitted through a fiber delay deviceand a second photo-detector; estimating one or more phase impairments inthe LiDAR system using the digitally-sampled reference signal to produceone or more estimated phase impairments; applying a first frequencyshift to the digitally-sampled target signal, the first frequency shiftbeing a function of the ego-velocity of the LIDAR system and anestimated target velocity; adjusting for phase impairments in thedigitally-sampled target signal for transmission to a point cloud usinga deskew filter; and applying a second frequency shift to thedigitally-sampled target signal, the second frequency shift being aconjugate of the first frequency shift. In an embodiment, adjusting forphase impairments in the digitally-sampled target signal includescorrecting for phase impairments introduced into the digitally-sampledtarget signal by the LO beam and by the return signal. In an embodiment,the method also includes determining a velocity of neighboring points ina vicinity of the target; and generating the estimated target velocitybased on the velocity of neighboring points. In an embodiment, themethod also includes determining a velocity of previous points of thetarget within a point cloud; and generating the estimated targetvelocity based on the velocity of previous points.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the various examples, reference isnow made to the following detailed description taken in connection withthe accompanying drawings in which like identifiers correspond to likeelements.

FIG. 1 illustrates an example LIDAR system according to embodiments ofthe present disclosure.

FIG. 2 is a time-frequency diagram illustrating how LIDAR waveforms aredetected and processed according to embodiments of the presentdisclosure.

FIG. 3A illustrates phase impairments that can be mitigated byembodiments of the present disclosure.

FIG. 3B illustrates dynamic scenarios in which impairments can becorrected by embodiments of the present disclosure.

FIG. 4 is a block diagram of an example LIDAR system with a referencearm, according to embodiments of the present disclosure.

FIG. 5 illustrates an ego-Doppler compensated corrector in accordancewith embodiments of the present disclosure.

FIG. 6 illustrates a neighborhood velocity based corrector in accordancewith embodiments of the present disclosure.

FIG. 7 illustrates a previous points based corrector in accordance withembodiments of the present disclosure.

FIG. 8 illustrates an iterative phase impairment corrector in accordancewith embodiments of the present disclosure.

FIG. 9 illustrates a multi-Doppler compensated corrector in accordancewith embodiments of the present disclosure.

FIG. 10 is a flow diagram of an example method of compensating for phaseimpairments within a LIDAR system, according to an embodiment of thepresent disclosure.

FIG. 11 is a flow diagram of another example method of compensating forphase impairments within a LIDAR system, according to an embodiment ofthe present disclosure.

DETAILED DESCRIPTION

The present disclosure describes various examples of LIDAR systems andmethods for compensating for phase impairments in dynamic scenesdetected by LIDAR systems. According to some embodiments, the describedLIDAR system may be implemented in any sensing market, such as, but notlimited to, transportation, manufacturing, metrology, medical, virtualreality, augmented reality, and security systems. According to someembodiments, the described LIDAR system is implemented as part of afront-end of frequency modulated continuous-wave (FMCW) device thatassists with spatial awareness for automated driver assist systems, orself-driving vehicles.

FIG. 1 illustrates a LIDAR system 100 according to exampleimplementations of the present disclosure. The LIDAR system 100 includesone or more of each of a number of components, but may include fewer oradditional components than shown in FIG. 1 . One or more of thecomponents depicted in FIG. 1 can be implemented on a photonics chip,according to some embodiments. According to some embodiments, the LIDARsystem 100 includes one or more components that can be implemented on aphotonics chip. The optical circuits 101 may include a combination ofactive optical components and passive optical components. Active opticalcomponents may generate, amplify, and/or detect optical signals and thelike. In some examples, the active optical component includes opticalbeams at different wavelengths, and includes one or more opticalamplifiers, one or more optical detectors, or the like.

Free space optics 115 may include one or more optical waveguides tocarry optical signals, and route and manipulate optical signals toappropriate input/output ports of the active optical circuit. The freespace optics 115 may also include one or more optical components such astaps, wavelength division multiplexers (WDM), splitters/combiners,polarization beam splitters (PBS), collimators, couplers or the like. Insome examples, the free space optics 115 may include components totransform the polarization state and direct received polarized light tooptical detectors using a PBS, for example. The free space optics 115may further include a diffractive element to deflect optical beamshaving different frequencies at different angles along an axis (e.g., afast-axis).

In some examples, the LIDAR system 100 includes an optical scanner 102that includes one or more scanning mirrors that are rotatable along anaxis (e.g., a slow-axis) that is orthogonal or substantially orthogonalto the fast-axis of the diffractive element to steer optical signals toscan an environment according to a scanning pattern. For instance, thescanning mirrors may be rotatable by one or more galvanometers. Objectsin the target environment may scatter an incident light into a returnoptical beam or a target return signal. The optical scanner 102 alsocollects the return optical beam or the target return signal, which maybe returned to the passive optical circuit component of the opticalcircuits 101. For example, the return optical beam may be directed to anoptical detector by a polarization beam splitter. In addition to themirrors and galvanometers, the optical scanner 102 may includecomponents such as a quarter-wave plate, lens, anti-reflective coatedwindow or the like.

To control and support the optical circuits 101 and optical scanner 102,the LIDAR system 100 includes LIDAR control systems 110. The LIDARcontrol systems 110 may include a processing device for the LIDAR system100. In some examples, the processing device may be one or moregeneral-purpose processing devices such as a microprocessor, centralprocessing unit, or the like. More particularly, the processing devicemay be complex instruction set computing (CISC) microprocessor, reducedinstruction set computer (RISC) microprocessor, very long instructionword (VLIW) microprocessor, or processor implementing other instructionsets, or processors implementing a combination of instruction sets. Theprocessing device may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like.

In some examples, the LIDAR control systems 110 may include a signalprocessing unit 112 such as a DSP. The LIDAR control systems 110 areconfigured to output digital control signals to control optical drivers103. In some examples, the digital control signals may be converted toanalog signals through signal conversion unit 106. For example, thesignal conversion unit 106 may include a digital-to-analog converter.The optical drivers 103 may then provide drive signals to active opticalcomponents of optical circuits 101 to drive optical sources such aslasers and amplifiers. In some examples, several optical drivers 103 andsignal conversion units 106 may be provided to drive multiple opticalsources.

The LIDAR control systems 110 are also configured to output digitalcontrol signals for the optical scanner 102. A motion control system 105may control the galvanometers of the optical scanner 102 based oncontrol signals received from the LIDAR control systems 110. Forexample, a digital-to-analog converter may convert coordinate routinginformation from the LIDAR control systems 110 to signals interpretableby the galvanometers in the optical scanner 102. In some examples, amotion control system 105 may also return information to the LIDARcontrol systems 110 about the position or operation of components of theoptical scanner 102. For example, an analog-to-digital converter may inturn convert information about the galvanometers' position to a signalinterpretable by the LIDAR control systems 110.

The LIDAR control systems 110 are further configured to analyze incomingdigital signals. In this regard, the LIDAR system 100 includes opticalreceivers 104 to measure one or more beams received by optical circuits101. For example, a reference beam receiver may measure the amplitude ofa reference beam from the active optical component, and ananalog-to-digital converter converts signals from the reference receiverto signals interpretable by the LIDAR control systems 110. Targetreceivers measure the optical signal that carries information about therange and velocity of a target in the form of a beat frequency,modulated optical signal. The reflected beam may be mixed with a signalfrom a local oscillator. The optical receivers 104 may include ahigh-speed analog-to-digital converter to convert signals from thetarget receiver to signals interpretable by the LIDAR control systems110. In some examples, the signals from the optical receivers 104 may besubject to signal conditioning by signal conditioning unit 107 prior toreceipt by the LIDAR control systems 110. For example, the signals fromthe optical receivers 104 may be provided to an operational amplifierfor amplification of the received signals and the amplified signals maybe provided to the LIDAR control systems 110.

In some applications, the LIDAR system 100 may additionally include oneor more imaging devices 108 configured to capture images of theenvironment, a global positioning system 109 configured to provide ageographic location of the system, or other sensor inputs. The LIDARsystem 100 may also include an image processing system 114. The imageprocessing system 114 can be configured to receive the images andgeographic location, and send the images and location or informationrelated thereto to the LIDAR control systems 110 or other systemsconnected to the LIDAR system 100.

In operation according to some examples, the LIDAR system 100 isconfigured to use nondegenerate optical sources to simultaneouslymeasure range and velocity across two dimensions. This capability allowsfor real-time, long range measurements of range, velocity, azimuth, andelevation of the surrounding environment.

In some examples, the scanning process begins with the optical drivers103 and LIDAR control systems 110. The LIDAR control systems 110instruct the optical drivers 103 to independently modulate one or moreoptical beams, and these modulated signals propagate through the passiveoptical circuit to the collimator. The collimator directs the light atthe optical scanning system that scans the environment over apreprogrammed pattern defined by the motion control system 105. Theoptical circuits 101 may also include a polarization wave plate (PWP) totransform the polarization of the light as it leaves the opticalcircuits 101. In some examples, the polarization wave plate may be aquarter-wave plate or a half-wave plate. A portion of the polarizedlight may also be reflected back to the optical circuits 101. Forexample, lensing or collimating systems used in LIDAR system 100 mayhave natural reflective properties or a reflective coating to reflect aportion of the light back to the optical circuits 101.

Optical signals reflected back from the environment pass through theoptical circuits 101 to the receivers. Because the polarization of thelight has been transformed, it may be reflected by a polarization beamsplitter along with the portion of polarized light that was reflectedback to the optical circuits 101. Accordingly, rather than returning tothe same fiber or waveguide as an optical source, the reflected light isreflected to separate optical receivers. These signals interfere withone another and generate a combined signal. Each beam signal thatreturns from the target produces a time-shifted waveform. The temporalphase difference between the two waveforms generates a beat frequencymeasured on the optical receivers (photodetectors). The combined signalcan then be reflected to the optical receivers 104.

The analog signals from the optical receivers 104 are converted todigital signals using ADCs. The digital signals are then sent to theLIDAR control systems 110. A signal processing unit 112 may then receivethe digital signals and interpret them. In some embodiments, the signalprocessing unit 112 also receives position data from the motion controlsystem 105 and galvanometers (not shown) as well as image data from theimage processing system 114. The signal processing unit 112 can thengenerate a 3D point cloud with information about range and velocity ofpoints in the environment as the optical scanner 102 scans additionalpoints. The signal processing unit 112 can also overlay a 3D point clouddata with the image data to determine velocity and distance of objectsin the surrounding area. The system also processes the satellite-basednavigation location data to provide a precise global location.

FIG. 2 is a time-frequency diagram 200 of an FMCW scanning signal 201that can be used by a LIDAR system, such as system 100, to scan a targetenvironment according to some embodiments. In one example, the scanningwaveform 201, labeled as fFM(t), is a sawtooth waveform (sawtooth“chirp”) with a chirp bandwidth ΔfC and a chirp period TC. The slope ofthe sawtooth is given as k=(ΔfC/TC). FIG. 2 also depicts target returnsignal 202 according to some embodiments. Target return signal 202,labeled as fFM(t−Δt), is a time-delayed version of the scanning signal201, where Δt is the round trip time to and from a target illuminated byscanning signal 201. The round trip time is given as Δt=2R/v, where R isthe target range and v is the velocity of the optical beam, which is thespeed of light c. The target range, R, can therefore be calculated asR=c(Δt/2). When the return signal 202 is optically mixed with thescanning signal, a range dependent difference frequency (“beatfrequency”) ΔfR(t) is generated. The beat frequency ΔfR(t) is linearlyrelated to the time delay Δt by the slope of the sawtooth k. That is,ΔfR(t)=kΔt. Since the target range R is proportional to Δt, the targetrange R can be calculated as R=(c/2)(ΔfR(t)/k). That is, the range R islinearly related to the beat frequency ΔfR(t). The beat frequency ΔfR(t)can be generated, for example, as an analog signal in optical receivers104 of system 100. The beat frequency can then be digitized by ananalog-to-digital converter (ADC), for example, in a signal conditioningunit such as signal conditioning unit 107 in LIDAR system 100. Thedigitized beat frequency signal can then be digitally processed, forexample, in a signal processing unit, such as signal processing unit 112in system 100. It should be noted that the target return signal 202will, in general, also includes a frequency offset (Doppler shift) ifthe target has a velocity relative to the LIDAR system 100. The Dopplershift can be determined separately, and used to correct the frequency ofthe return signal, so the Doppler shift is not shown in FIG. 2 forsimplicity and ease of explanation. It should also be noted that thesampling frequency of the ADC will determine the highest beat frequencythat can be processed by the system without aliasing. In general, thehighest frequency that can be processed is one-half of the samplingfrequency (i.e., the “Nyquist limit”). In one example, and withoutlimitation, if the sampling frequency of the ADC is 1 gigahertz, thenthe highest beat frequency that can be processed without aliasing(ΔfRmax) is 500 megahertz. This limit in turn determines the maximumrange of the system as Rmax=(c/2)(ΔfRmax/k) which can be adjusted bychanging the chirp slope k. In one example, while the data samples fromthe ADC may be continuous, the subsequent digital processing describedbelow may be partitioned into “time segments” that can be associatedwith some periodicity in the LIDAR system 100. In one example, andwithout limitation, a time segment might correspond to a predeterminednumber of chirp periods T, or a number of full rotations in azimuth bythe optical scanner.

In some scenarios, there may be several sources of phase impairmentsexperienced by LIDAR systems, such as the LIDAR system described at FIG.1 . Examples of these sources may be laser phase noise, circuitry phasenoise, flicker noise that the driving electronics inject on the laser,drift over temperature/weather, or chirp rate offsets.

FIG. 3A illustrates phase impairments that can be mitigated byembodiments of the present invention. A phase impairment corrected peak301 is shown corresponding to a non-corrected peak 303. As shown in FIG.3A, the phase impairment on the received signal depends on the range ofthe target. In some scenarios, targets that are further away may have ahigher bandwidth of phase impairment compared to closer targets. Forexample, the farthest non-corrected peak 305 shown in FIG. 3A has asignificantly higher bandwidth of phase impairment compared to thecloser non-corrected peak 307. In some scenarios, a phase impairment maydepend only on range and not on Doppler shift, whereas peak frequencymay depend on both range and Doppler shift. In some embodiments, thedependency of phase impairment on range may be utilized in somecorrection algorithms described herein. In some embodiments, a deskewfilter can be used to apply a negative group delay which may be linearlyproportional to the frequency.

FIG. 3B illustrates dynamic scenarios that can be mitigated byembodiments of the present invention. As shown in FIG. 3B, the peakfrequency 311 can be calculated as frequency=alpha (times) Δt (plus orminus) a Doppler shift 309, where alpha is the slope of the chirp (alsocalled chirp rate). In some embodiments, a deskew filter appliesnegative group delay based on alpha (times) Range (plus or minus)Doppler shift instead of alpha (times) Range. This may lead to a loss inperformance and a loss in probability of detection and range/velocityerror on dynamic targets.

The embodiments described herein address these issues by, for example,utilizing the described ego-Doppler compensated phase impairmentcorrector. The ego-Doppler compensated phase impairment corrector maycompensate for ego-velocity before applying a deskew filter. It shouldbe noted that ego-velocity as described herein can include, but is notlimited to, both vehicle velocity, sensor velocity, mirror velocity, andthe like, or any previous ego-velocity determinations made by, orprovided to, the systems described herein as well as any combination ofthem. As used herein, the ego-velocity can be estimated using either thepoint cloud, or it can be measured using one or more motions sensors,such as an inertial measurement unit (IMU).

In some embodiments, a neighborhood velocity-based phase impairmentcorrector can be used, as discussed in more detail below in reference toFIG. 6 . A signal may be run through a deskew filter, an estimate of thetrue target velocity may be derived using the velocity of a subset ofall detected points in the neighborhood using the standard deskew filterand then re-perform correction procedures based on a neighborhoodvelocity estimate.

In some embodiments, a previous-points-based phase impairment correctorcan be used. The previous-points-based phase impairment corrector mayuse the velocity from previous estimated points to estimate the mostlikely velocity of the current point and apply that frequency shiftbefore a deskew compensation. In some embodiments, immediate previouspoints may be used. In embodiments, points from previous scan lines maybe used. In some embodiments, points from previous frames may be used.

In some embodiments, an iterative phase impairment corrector and/or amulti-Doppler compensated phase impairment corrector can be used. Insome embodiments, Doppler compensation may be applied to any of thedescribed techniques on either target ADC samples or on deskew filtercoefficients.

FIG. 4 is a block diagram of an example LIDAR system with a referencearm 427, according to embodiments of the present disclosure. As shown inFIG. 4 , according to some embodiments, one or more reference arms 427can be added to a LIDAR system to generate a digitally-sampled referencesignal 426 that can be used to estimate the phase impairment intransmitted signals. For instance, in one embodiment, one or morereference arms 427 can be included as part of optical circuits 101,signal conversion unit 106, and/or signal conversion unit 107 in FIG. 1. In this example embodiment, the system includes a beam source 401,such as a FMCW laser source. The target arm 405 includes a number ofoptical components (e.g. lenses or filters) through which the scanningsignal 403 can pass on its way to a target 407. The return signal 409can be reflected from the target 407 and directed to a photo detector411. In this embodiment, a local oscillator (LO) signal 413, which is aportion of the scanning signal 403, is directed to the photo detector411 before being sent out to the target 407. From the photo detector411, a digitally-sampled target signal 416 then passes to a target ADC415, and then to the DSP 417.

As depicted in this embodiment, the reference arm 427 receives a signalportion 419 of the scanning signal 403, which can be provided to a photodetector 421 directly, and also after passing through a delay device 423having a known length. According to some embodiments, signal portion 419is received by photo detector 421 as scanning signal 403 is transmittedcontemporaneously through the optical components of target arm 405.According to some embodiments, signal portion 419 is received by photodetector 421 after scanning signal 403 is transmitted through theoptical components of target arm 405. According to some embodiments,delay device 423 can be a fiber delay device, etc. In one embodiment,the delay device 423 can include a fiber coil with a known length thatcan create a virtual target (e.g., fiber target) at a known distance.

In some scenarios, the virtual target's distance can be pre-determined.The optical signal at the output of the reference delay has the samecharacteristics as the target return signal 202 depicted in FIG. 2 .According to some embodiments, in a manner similar to that described inFIG. 2 , the virtual target can produce a return signal 409 that is atime-delayed version of scanning signal 403. When the return signal 409is optically mixed with the scanning signal 603, a reference rangedependent difference frequency (“reference beat frequency”) isgenerated. According to some embodiments, the reference beat frequencycan then be digitized and conditioned using the procedures describedherein, for example, in FIG. 1 . This reference signal has the samesignature of phase impairment as the reference signal from the target. Aphase impairment estimator, based at least in part on the referencesignal produced by reference arm 427 and a phase impairments correctorcan compensate for phase impairments in signals transmitted towards atarget (i.e., “target” signals) and signals received therefrom (i.e.,“received” signals).

From the photo detector 421, the digitally-sampled reference signal 426then passes to a reference ADC 425 and then to the DSP 417. As shown inFIG. 4 , embodiments of the present invention can produce point clouddata 429 based on the transmission and receipt of various signals,including the return signal 409 from a target, a LO signal 413, and areference arm 427.

FIG. 5 illustrates an ego-Doppler compensated corrector in accordancewith embodiments of the present invention. As depicted in FIG. 5 , thephase impairments corrector 509 is configured with an ego-Dopplercompensated corrector configured to compensate for an estimated ormeasured ego-Doppler by introducing a frequency shift provided, by afrequency shifter 507, on the received signal before running a deskewfilter 508 and undoing the frequency shift at frequency shifter 511after a phase impairment correction. In some embodiments, theego-Doppler compensated corrector can be applied to static targets in agiven scene.

As shown in FIG. 5 , a phase impairments estimator 503, a phaseimpairments corrector 509, along with one or more reference ADCs 501 andtarget ADCs 505 can correspond to the DSP 417 of FIG. 4 , in someembodiments. According to one embodiment, one or more of phaseimpairments estimator 503 and/or phase impairments corrector 509 can beincluded as part of signal processing unit 112 in FIG. 1 . In someembodiments, the architecture also includes time domain filters 513,time domain (TD) to frequency domain (FD) converters 515, frequencydomain filters 517, and peak picking components 519. The digital signalprocessing architecture can generate and process data such as pointcloud data 521. It should be appreciated that, although the use of pointclouds are described herein, embodiments are not limited to such and mayinclude, but are not limited to, point sets.

FIG. 6 illustrates a neighborhood velocity-based corrector used by aphase impairments corrector in accordance with embodiments of thepresent invention. As shown in FIG. 6 , phase impairments corrector 609is configured with a neighborhood velocity-based corrector that runs aphase impairments corrector 623 on a subset of all points and estimatesvelocity based on neighborhood points using a neighborhood estimator633. In some embodiments, the estimate can be the mean/median or anyother statistic of the velocity of neighboring points. In alternativeembodiments, the neighborhood velocity-based corrector may compensatefor estimated Doppler shift and rerun the phase impairment corrector tore-estimate the peaks.

Once the neighborhood velocity has been estimated, an estimated Dopplershift can be calculated by a Doppler shift estimator 635, and anassociated frequency shift introduced at frequency shifter 607 beforethe deskew filter 608 and phase impairments corrector 609. As describedabove, a deskew filter 608 applies a variable delay based on frequency,so an adjustment to the frequency introduced at frequency shifter 607impacts the delay applied by the deskew filter 608. In some embodiments,the second frequency shift applied at frequency shifter 611 is aconjugate of the first frequency shift introduced at frequency shifter607.

As shown in FIG. 6 , the digital signal processing architecture includesa phase impairments estimator 603, a phase impairments corrector 609,along with one or more reference ADCs 601 and target ADCs 605. In someembodiments, the neighborhood velocity estimator arm also includes timedomain filters 625, TD to FD converters 627, frequency domain filters629, and peak picking components 631. Similarly, the architecture of thetarget arm can also include time domain filters 613, TD to FD converters615, frequency domain filters 617, and peak picking components 619. Thedigital signal processing architecture can generate and process datasuch as point cloud data 621.

FIG. 7 illustrates a previous-points-based corrector in accordance withembodiments of the present invention. As shown in FIG. 7 , the phaseimpairments corrector 709 is configured with a previous-points-basedcorrector that is configured to estimate the velocity of a point basedon previously estimated points. In some embodiments, immediate previouspoints may be used. In some embodiments, points from previous scan linesmay be used. In embodiments, points from previous frames may be used.The previous-points-based corrector may be used to estimate velocity tocompensate for Doppler shift prior to the phase impairment corrector.

As shown in FIG. 7 , the digital signal processing architecture includesa phase impairments estimator 703, a phase impairments corrector 709,along with one or more reference ADCs 701 and target ADCs 705. In someembodiments, the architecture of the target arm can also includetime-domain filters 713, TD to FD converters 715, frequency-domainfilters 717, and peak picking components 719. The digital signalprocessing architecture can generate and process data such as pointcloud data 721. In this example embodiment, after peak picking 719, avelocity estimator 723 estimates the velocity of the previous points, asdescribed above. Based on this velocity estimation, an associatedfrequency shift can be introduced at 707 before the deskew filter 708and phase impairments corrector 709. As described above, a deskew filter708 applies a variable delay based on frequency, so an adjustment to thefrequency introduced at frequency shifter 707 impacts the delay appliedby the deskew filter 708. In some embodiments, the second frequencyshift applied at frequency shifter 711 is a conjugate of the firstfrequency shift introduced at frequency shifter 707.

FIG. 8 illustrates an iterative phase impairment corrector in accordancewith embodiments of the present invention. As shown in FIG. 8 , phaseimpairments corrector 807 is configured with an iterative phaseimpairment corrector may iterate through a loop multiple times untilconvergence. As shown in FIG. 8 , the digital signal processingarchitecture includes a phase impairments estimator 801, computation offilter taps 803, and a phase impairments corrector 807. In someembodiments, the architecture of the target arm can also include timedomain filters 811, TD to FD converters 813, frequency domain filters815, and peak picking components 817.

In this example embodiment, a first frequency shift is introduced atfrequency shifter 805 before a deskew filter 808 and the phaseimpairments corrector 807. A second frequency shift can be introduced atfrequency shifter 809, and the second frequency shift can be a conjugateof the first frequency shift from frequency shifter 805. In this exampleembodiment, after peak picking 817, the process is iterated with adifferent frequency shift introduced at frequency shifter 805 andfrequency shifter 809 until convergence is achieved. For each iteration,a velocity estimate from the previous iteration is used to apply afrequency shift. Thus, for each iteration, the selected peaks and thecorresponding range and velocity estimates could be different.Convergence can be achieved if the selected peaks are the same over twoor more consecutive iterations.

FIG. 9 illustrates a multi-Doppler compensated corrector in accordancewith embodiments of the present invention. As shown in FIG. 9 , phaseimpairments correctors 909, 927 are each configured with a multi-Dopplercompensated corrector that performs phase impairment correction for anumber (N) of different Doppler compensated received signals and pickthe best.

As shown in FIG. 9 , the digital signal processing architecture includesa phase impairments estimator 703, a number of phase impairmentscorrectors 909, 927, along with one or more reference ADCs 901 andtarget ADCs 905. In this particular embodiment, the received signal 904is diverted to a number of different paths, where each path includes adifferent frequency shift. For example, a first frequency shift can beintroduced at frequency shifter 907 ahead of the first deskew filter 908and the first phase impairments corrector 909. After the first phaseimpairments corrector 909, the frequency shift introduced at frequencyshifter 907 can be reversed at frequency shifter 911. In someembodiments, this first target arm can also include time-domain filters913, TD to FD converters 915, frequency-domain filters 917, and peakpicking components 919. Similarly, the Nth target arm can include a Nthfrequency shift introduced at frequency shifter 923 ahead of the Nthdeskew filter 925 and the Nth phase impairments corrector 927. After theNth phase impairments corrector 927, the frequency shift introduced atfrequency shifter 923 can be reversed at frequency shifter 929. In someembodiments, the Nth target arm can also include time domain filters931, TD to FD converters 933, frequency-domain filters 935, and peakpicking components 937. Finally, once a peak has been picked for each ofthe several delays, the best peak can be chosen at 921. Selecting theoptimal peak may include, in some embodiments, picking the strongestpeak, the highest SNR, or other metrics that are used for signaldetection.

FIG. 10 is a flow diagram of an example method of compensating for phaseimpairments within a LIDAR system, according to an embodiment of thepresent disclosure. The method begins at operation 1001 by transmittinga first optical beam to a target. The first optical beam can include,for example, a FMWC beam. In an embodiment, the optical beam can betransmitted from a beam source 401.

At operation 1003, a return signal 409 is received from the target at afirst detector. The first detector that receives the return signal 409may be the photo detector 411 discussed above in reference to FIG. 4 .

At operation 1005, a digitally-sampled target signal 416 is generatedusing a local oscillator (LO) beam 413, a photo detector 411, and thereturn signal 409.

At operation 1007, the ego-velocity and target velocity is compensatedfor in the digitally-sampled target signal 416 based on an estimatedego-velocity and an estimated target velocity. This compensation can beperformed, in some embodiments, using frequency shifters 507, 511, 607,611, 707, 711, 805, 809, 907, 911, 923, 929. In one embodiment, a firstfrequency shift can be applied to the digitally-sampled target signal,where the first frequency shift is a function of the ego-velocity of theLIDAR system and an estimated target velocity. A second frequency shiftcan be applied to the digitally-sampled target signal that is aconjugate of the first frequency shift. In some embodiments, theestimated target velocity is based on the velocity of neighboringpoints, and the velocity of neighboring points can be determined byrunning a standard corrector on all neighboring points and estimating astatistic (e.g., mean or median) of the velocity of neighboring points.In other embodiments, the estimated target velocity is based on thevelocity of previous points.

At operation 1009, a phase impairment correction is performed on thedigitally-sampled target signal using a phase impairments corrector 509,609, 709, 807, 909, 927. In some embodiments, the method also includesgenerating a digitally-sampled reference signal using a reference beamtransmitted through a fiber delay device having a known length. Thephase impairment correction can correct phase impairments introducedinto the digitally-sampled target signal by the LO beam and by thereturn signal. In such an embodiment, the reference beam can be splitfrom the first optical beam using a beam splitter. In some embodiments,adjusting for the phase impairments in the return signal includesintroducing a delay to the return signal based on a frequency of thereturn signal. Such a delay can be proportional to the frequency of thereturn signal, such that reflections from targets at a larger distanceare delayed more, and reflections from targets at a shorter distance aredelayed less. This delay can be introduced using, for example, a deskewfilter 508, 608, 708, 808, 908, 925.

FIG. 11 is a flow diagram of another example method of compensating forphase impairments within a LIDAR system, according to an embodiment ofthe present disclosure. The method begins at operation 1101 by receivinga return signal 409 reflected from a target 407 at a LIDAR system. Thereturn signal 409 is a reflection of a first optical beam 403transmitted from the LIDAR system. The optical beam 403 can betransmitted using a beam source 401, in some embodiments.

At operation 1103, the method determines an ego-velocity of the LIDARsystem. In some embodiments, the ego-velocity is a velocity of the LIDARsystem with respect to neighboring objects. The ego-velocity can alsoinclude the velocity of a mirror associated with the LIDAR system. Insome embodiments, the ego-velocity of the LIDAR system can bedetermined, for example, using the signal processing unit 112 or themotion control system 105, described in reference to FIG. 1 .

At operation 1105, the method determines an estimated target velocity.In some embodiments, determining the estimated target velocity includesdetermining the velocity of neighboring points in the vicinity of thetarget; and generating the estimated target velocity based on thevelocity of neighboring points. In some embodiments, estimating thevelocity of neighboring points includes running a standard corrector onall neighboring points; and estimating a statistic (e.g., mean ormedian) of the velocity of neighboring points. In alternativeembodiments, determining the estimated target velocity includesdetermining the velocity of previous points of the target within a pointcloud, and generating the estimated target velocity based on thevelocity of the previous points. In some embodiments, the previouspoints can include an immediately preceding point in the same scan line,or the velocity of points from previous scan lines or previousscan-frames. In some embodiments, the estimated target velocity can bedetermined, for example, using the signal processing unit 112 or theimage processing system 114, described in reference to FIG. 1 .

At operation 1107, an estimated phase impairment is calculated using aphase impairments estimator 503, 603, 703, 801, 903. At operation 1109,a first frequency shift is applied to the return signal. In someembodiments, the first frequency shift is a function of the ego-velocityof the LIDAR system. In some embodiments, the first frequency shift is afunction of the estimated target velocity determined at operation 1105.

Once the first frequency shift has been applied, the return signal isadjusted at operation 1111 to account for phase impairments, based onthe estimated phase impairment. In some embodiments, adjusting for thephase impairments in the return signal includes introducing a delay tothe return signal based on a frequency of the return signal. Such adelay can be proportional to the frequency of the return signal, suchthat reflections from targets at a larger distance are delayed more, andreflections from targets at a shorter distance are delayed less. Thisdelay can be introduced using, for example, a deskew filter 508, 608,708, 808, 908, 925.

At operation 1113, a second frequency shift is applied to the delayedbeam from the deskew filter. In some embodiments, the second frequencyshift is a conjugate of the first frequency shift. The frequency shiftsperformed at operations 1109 and 1113 can be performed, for example,using frequency shifters 507, 511, 607, 611, 707, 711, 805, 809, 907,911, 923, 929.

The preceding description sets forth numerous specific details such asexamples of specific systems, components, methods, and so forth, inorder to provide a thorough understanding of several examples in thepresent disclosure. It will be apparent to one skilled in the art,however, that at least some examples of the present disclosure may bepracticed without these specific details. In other instances, well-knowncomponents or methods are not described in detail or are presented insimple block diagram form in order to avoid unnecessarily obscuring thepresent disclosure. Thus, the specific details set forth are merelyexemplary. Particular examples may vary from these exemplary details andstill be contemplated to be within the scope of the present disclosure.

Any reference throughout this specification to “one example” or “anexample” means that a particular feature, structure, or characteristicdescribed in connection with the examples are included in at least oneexample. Therefore, the appearances of the phrase “in one example” or“in an example” in various places throughout this specification are notnecessarily all referring to the same example.

The term “coupled,” along with its derivatives, is used to indicate thattwo or more elements interact with each other. These coupled elementsmay or may not be in direct physical or electrical contact with eachother.

Although the operations of the methods herein are shown and described ina particular order, the order of the operations of each method may bealtered so that certain operations may be performed in an inverse orderor so that certain operation may be performed, at least in part,concurrently with other operations. Instructions or sub-operations ofdistinct operations may be performed in an intermittent or alternatingmanner.

The above description of illustrated implementations of the invention,including what is described in the Abstract, is not intended to beexhaustive or to limit the invention to the precise forms disclosed.While specific implementations of, and examples for, the invention aredescribed herein for illustrative purposes, various equivalentmodifications are possible within the scope of the invention, as thoseskilled in the relevant art will recognize. The words “example” or“exemplary” are used herein to mean serving as an example, instance, orillustration. Any aspect or design described herein as “example” or“exemplary” is not necessarily to be construed as preferred oradvantageous over other aspects or designs. Rather, use of the words“example” or “exemplary” is intended to present concepts in a concretefashion. As used in this application, the term “or” is intended to meanan inclusive “or” rather than an exclusive “or”. That is, unlessspecified otherwise, or clear from context, “X includes A or B” isintended to mean any of the natural inclusive permutations. That is, ifX includes A; X includes B; or X includes both A and B, then “X includesA or B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform. Furthermore, the terms “first,” “second,” “third,” “fourth,” etc.as used herein are meant as labels to distinguish among differentelements and may not necessarily have an ordinal meaning according totheir numerical designation.

What is claimed is:
 1. A method of compensation in a light detection andranging (LIDAR) system comprising: generating a digitally-sampled targetsignal; and compensating for ego-velocity and target velocity in thedigitally-sampled target signal based on an estimated ego-velocity andan estimated target velocity to produce a compensated digitally-sampledtarget signal, wherein the ego-velocity comprises a velocity of theLIDAR system with respect to one or more objects positioned relative tothe LIDAR system.
 2. The method of claim 1, further comprising:performing a phase impairment correction on the compensateddigitally-sampled target signal for transmission to a point cloud. 3.The method of claim 1, further comprising: transmitting a first opticalbeam towards a target; and receiving, based on the first optical beam, asecond optical beam from the target to produce a return signal.
 4. Themethod of claim 3, wherein generating the digitally-sampled targetsignal is performed using a local oscillator (LO) beam, a firstphoto-detector, and the return signal.
 5. The method of claim 1, furthercomprising: determining the ego-velocity of the LIDAR system, whereinthe ego-velocity is a velocity of the LIDAR system calculated based onneighboring objects measured using one or more motion sensors.
 6. Themethod of claim 1, wherein compensating for the ego-velocity and targetvelocity in the digitally-sampled target signal further comprises:applying a first frequency shift to the digitally-sampled target signal,the first frequency shift being a function of an ego-velocity of theLIDAR system; and applying a second frequency shift to thedigitally-sampled target signal, the second frequency shift being aconjugate of the first frequency shift.
 7. The method of claim 1,further comprising: determining a velocity of neighboring points in avicinity of a target; and generating the estimated target velocity basedon the velocity of neighboring points.
 8. The method of claim 2, furthercomprising: determining a velocity of previous points of the targetwithin a point cloud; and generating the estimated target velocity basedon the velocity of previous points.
 9. A light detection and ranging(LIDAR) system comprising: an optical source to transmit an optical beamtoward a target; an optical detector to generate a digitally-sampledtarget signal from a reflection of the optical beam from the target; atleast two frequency shifters to compensate for ego-velocity and targetvelocity in the digitally-sampled target signal based on an estimatedego-velocity and estimated target velocity, wherein the ego-velocitycomprises a velocity of the LIDAR system with respect to one or moreobjects positioned relative to the LIDAR system; and a deskew filter toperform a phase impairment correction on the digitally-sampled targetsignal.
 10. The system of claim 9, further comprising: an optical beamsource to transmit a first optical beam to a target; and a first photodetector to receive a return signal from the target and a localoscillator (LO) beam and generate the digitally-sampled target signal.11. The system of claim 10, further comprising: a fiber delay devicehaving a known length; and a second detector coupled to the fiber delaydevice to generate a digitally-sampled reference signal using areference beam transmitted through the fiber delay device.
 12. Thesystem of claim 9, wherein the ego-velocity is a velocity of the LIDARsystem with respect to neighboring objects measured using one or moremotion sensors.
 13. The system of claim 9, wherein the at least twofrequency shifters comprise: a first frequency shifter to apply a firstfrequency shift to the digitally-sampled target signal, the firstfrequency shift being a function of an ego-velocity of the LIDAR system;and a second frequency shifter to apply a second frequency shift to thedigitally-sampled target signal, the second frequency shift being aconjugate of the first frequency shift.
 14. The system of claim 9,wherein the phase impairment correction on the digitally-sampled targetsignal corrects for phase impairments introduced into thedigitally-sampled target signal.
 15. The system of claim 9, wherein theLIDAR system is further configured to determine the estimated targetvelocity based on a velocity of neighboring points in a vicinity of atarget.
 16. The system of claim 9, wherein the LIDAR system is furtherconfigured to determine the estimated target velocity based on avelocity of previous points of the target within a point cloud.
 17. Amethod of compensation in a light detection and ranging (LIDAR) systemcomprising: applying a first frequency shift to a digitally-sampledtarget signal, the first frequency shift being a function of anego-velocity of the LIDAR system and an estimated target velocity;adjusting for phase impairments in the digitally-sampled target signalfor transmission to a point cloud; and applying a second frequency shiftto the digitally-sampled target signal, the second frequency shift beinga conjugate of the first frequency shift.
 18. The method of claim 17,further comprising estimating the phase impairments in the using adigitally-sampled reference signal.
 19. The method of claim 18, furthercomprising: determining a velocity of neighboring points in a vicinityof a target; and generating the estimated target velocity based on thevelocity of neighboring points.
 20. The method of claim 17, furthercomprising: determining a velocity of previous points of a target withinthe point cloud; and generating the estimated target velocity based onthe velocity of previous points.